Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A building manager comprising: a communications interface configured to receive time-of-use pricing information from a smart energy grid; and a processing circuit comprising a processor and non-transitory computer-readable medium with instructions executable by the processor stored thereon, the non-transitory computer-readable medium comprising: an integrated control layer configured to receive inputs from at least one building subsystem and to provide an output to the at least one building subsystem, the integrated control layer including at least one control algorithm module configured to process the inputs and to determine outputs; a demand response layer configured to process the time-of-use pricing information received from the smart energy grid to automatically determine which of a plurality of energy storage devices to operate and determine adjusted setpoints for one or more of the energy storage devices, the adjusted setpoints comprising setpoint energy transfer rates into one or more of the energy storage devices and out of one or more of the energy storage devices; wherein the at least one control algorithm module of the integrated control layer is configured to use the setpoint energy transfer rates to generate control signals for the at least one building subsystem and provide the control signals as the outputs to the at least one building subsystem.
Building energy management and optimization. This invention addresses the need to efficiently manage building energy consumption in response to dynamic electricity pricing from a smart energy grid. The system is a building manager that includes a communications interface for receiving time-of-use pricing information from a smart energy grid. It also has a processing circuit containing a processor and non-transitory computer-readable storage. This storage holds instructions for an integrated control layer and a demand response layer. The integrated control layer receives inputs from building subsystems and provides outputs to them. It contains control algorithm modules that process these inputs to determine outputs. The demand response layer processes the time-of-use pricing information. It automatically decides which of multiple energy storage devices to operate and sets adjusted setpoints for these devices. These setpoints define energy transfer rates into and out of the storage devices. Crucially, the control algorithm modules within the integrated control layer utilize the determined setpoint energy transfer rates. They use these rates to generate control signals for the building subsystems, which are then provided as outputs to those subsystems. This allows for automated adjustments to building operations based on energy pricing.
2. The building manager of claim 1 , further comprising: an enterprise applications layer configured to provide a building occupant interface to at least one building occupant.
This invention relates to building management systems that integrate enterprise applications to enhance occupant interactions. The system includes a building manager that interfaces with various building subsystems, such as HVAC, lighting, and security, to monitor and control building operations. The building manager further includes an enterprise applications layer that provides a user interface for building occupants. This interface allows occupants to interact with the building systems, such as adjusting temperature settings, controlling lighting, or accessing security features, through a centralized platform. The enterprise applications layer may also integrate with external enterprise systems, such as scheduling software or energy management platforms, to streamline building operations and improve occupant experience. The system aims to provide a unified, user-friendly interface that consolidates building management functions and enhances communication between occupants and building systems. This integration improves efficiency, reduces energy consumption, and enhances occupant comfort and security.
3. The building manager of claim 1 , comprising: an automated measurement and validation layer configured to measure energy use or track energy savings based on representations of the inputs stored in memory according to an international performance management and verification protocol (IPMVP).
4. The building manager of claim 3 , further comprising: an enterprise applications layer configured to provide services to enterprise level applications for communicating with the integrated control layer, the demand response layer, and the automated measurement and validation layer.
5. The building manager of claim 3 , wherein the automated measurement and validation layer is configured to monitor energy consumption for a building based on the inputs from the building subsystem.
6. The building manager of claim 5 , wherein the automated measurement and validation layer completes a calculation of energy consumption for the building without using inputs from a utility meter or power provider.
7. The building manager of claim 6 , wherein the automated measurement and validation layer is configured to validate energy use information provided by a utility or meter using the calculation of energy consumption for the building that is calculated without using the inputs from the utility meter or power provider.
8. The building manager of claim 3 , wherein the automated measurement and validation layer is included within a server that includes both the integrated control layer and the demand response layer.
9. The building manager of claim 1 , wherein the demand response layer is configured to monitor and control a power switching device to rout power to one or more destinations from the one or more of the energy storage devices.
10. The building manager of claim 9 , wherein the demand response layer is configured to controllably shift energy loads from peak to off peak times using the energy storage devices.
11. The building manager of claim 10 , wherein the demand response layer is configured to shed energy loads associated with the at least one building subsystem using one or more of the energy storage devices based on a signal received during peak times.
12. The building manager of claim 11 , wherein the signal is one of a high price signal and a contracted curtailment signal.
13. The building manager of claim 1 , wherein the energy storage devices include at least one of a battery, a thermal energy storage tank and one or more plug-in hybrid electric vehicles.
This invention relates to building energy management systems that integrate multiple energy storage devices to optimize energy usage and reduce costs. The system addresses the challenge of efficiently managing energy supply and demand in buildings by leveraging diverse storage technologies. The building manager coordinates energy storage devices, including batteries, thermal energy storage tanks, and plug-in hybrid electric vehicles (PHEVs). Batteries store electrical energy for later use, thermal storage tanks retain heat or cold for HVAC systems, and PHEVs act as mobile storage units that can supply power to the building when parked and connected. The manager dynamically allocates energy between these storage options based on real-time conditions, such as grid pricing, renewable energy availability, and building demand. This integration allows for peak demand reduction, cost savings, and improved grid stability by shifting energy usage to off-peak hours or utilizing stored energy during high-cost periods. The system also supports renewable energy integration by storing excess solar or wind power for later use. By combining these storage technologies, the invention provides a flexible and resilient energy management solution for buildings.
14. The building manager of claim 1 , wherein the integrated control layer is configured to use inputs from the smart energy grid, building energy loads, and/or building energy storage in a control algorithm configured to reduce energy costs based on the inputs.
This invention relates to building energy management systems that optimize energy usage to reduce costs. The system includes an integrated control layer that processes real-time data from multiple sources to dynamically adjust building energy consumption. The control layer receives inputs from a smart energy grid, which provides information on electricity pricing, demand response signals, and grid stability conditions. It also gathers data from building energy loads, such as HVAC systems, lighting, and appliances, to monitor their energy consumption patterns. Additionally, the system integrates inputs from building energy storage systems, such as batteries or thermal storage, to manage energy storage and discharge cycles. The control algorithm analyzes these inputs to predict energy costs and optimize building operations accordingly. For example, it may shift energy-intensive tasks to off-peak hours when electricity prices are lower or store excess energy during periods of low demand. The system aims to minimize energy expenses while maintaining occupant comfort and operational efficiency. This approach leverages smart grid capabilities and on-site energy storage to create a responsive, cost-effective energy management solution.
15. The building manager of claim 14 , wherein the demand response layer is configured to adjust or affect the control algorithm of the integrated control layer by planning a control strategy based on received real time pricing (RTP) information or forecasted pricing information for energy from a utility.
This invention relates to a building management system that optimizes energy consumption based on real-time or forecasted energy pricing. The system includes an integrated control layer that manages building operations such as HVAC, lighting, and other energy-consuming systems. A demand response layer interacts with the integrated control layer to modify its control algorithms. The demand response layer receives real-time pricing (RTP) or forecasted pricing data from a utility provider and uses this information to plan and implement a control strategy. This strategy adjusts the building's energy usage to reduce costs by shifting consumption to lower-priced periods or reducing demand during peak pricing times. The system may also incorporate weather forecasts, occupancy data, and other factors to refine the control strategy. The goal is to balance energy efficiency, occupant comfort, and cost savings by dynamically adjusting building operations in response to fluctuating energy prices. The invention aims to provide a more responsive and cost-effective approach to building energy management compared to traditional static control systems.
16. The building manager of claim 15 , wherein the demand response layer is further configured to calculate an estimate of demand loads for the building for upcoming time periods based on at least one of historical information, forecasted pricing, scheduled facility control events, and the inputs from the building subsystem.
17. The building manager of claim 16 , wherein the demand response layer is further configured to provide the calculated estimate of demand loads for the building to the smart energy grid for an energy provider.
18. The building manager of claim 14 , wherein the demand response layer is configured to automatically adjust or affect the control algorithm of the integrated control layer using model predictive control.
19. A building manager comprising: a communications interface configured to receive time-of-use pricing information from a smart energy grid; and a processing circuit comprising a processor and non-transitory computer-readable medium with instructions executable by the processor stored thereon, the non-transitory computer-readable medium comprising: an integrated control layer configured to receive inputs from at least one building subsystem and to provide outputs to the at least one building subsystem, the integrated control layer including at least one control algorithm module configured to process the inputs and to determine the outputs; and a demand response layer configured to process the time-of-use pricing information received from the smart energy grid to automatically determine which of a plurality of energy storage devices to operate and determine adjusted setpoints for one or more of the energy storage devices, the adjusted setpoints comprising setpoint energy transfer rates into the one or more energy storage devices and out of one or more of the energy storage devices, the demand response layer further configured to automatically adjust or affect one or more of the at least one control algorithm module using model predictive control; wherein the at least one control algorithm module of the integrated control layer is configured to use the setpoint energy transfer rates to generate control signals for the at least one building subsystem and provide the control signals as the outputs to the at least one building subsystem.
20. A building manager comprising: a communications interface configured to receive time-of-use pricing information from a smart energy grid; and a processing circuit comprising a processor and non-transitory computer-readable medium with instructions executable by the processor stored thereon, the non-transitory computer-readable medium comprising: an integrated control layer configured to receive inputs from at least one building subsystem and to provide outputs to the at least one building subsystem, the integrated control layer including at least one control algorithm module configured to process the inputs and to determine the outputs; and a demand response layer configured to process the time-of-use pricing information received from the smart energy grid automatically determine which of a plurality of energy storage devices to operate and to determine adjusted setpoints for one or more of the energy storage devices, the adjusted setpoints comprising setpoint energy transfer rates into one or more of the energy storage devices and out of one or more of the energy storage devices, the demand response layer further configured to controllably shift energy loads from peak to off peak times using the energy storage devices; wherein the at least one control algorithm module of the integrated control layer is configured to use the adjusted setpoints to generate control signals for the at least one building subsystem and provide the control signals as the outputs to the at least one building subsystem.
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January 26, 2021
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